Numerical simulations of contaminant dispersion, as after a gas leakage incident on a chemical plant, can provide valuable insights for both emergency response and preparedness. Simulation approaches combine incompressible Navier-Stokes (INS) equations with advection-diffusion (AD) processes to model wind and concentration field. However, the computational cost of such high-fidelity simulations increases rapidly for complex geometries like urban environments, making them unfeasible in time-critical or multi-query "what-if" scenarios. Therefore, this study focuses on the application of model order reduction (MOR) techniques enabling fast yet accurate predictions. To this end, a thorough comparison of intrusive and non-intrusive MOR methods is performed for the computationally more demanding parametric INS problem with varying wind velocities. Based on these insights, a non-intrusive reduced-order model (ROM) is constructed accounting for both wind velocity and direction. The study is conducted on a two-dimensional domain derived from real-world building footprints, preserving key features for analyzing the dispersion of, for instance, denser contaminants. The resulting ROM enables faster than real-time predictions of spatio-temporal contaminant dispersion from an instantaneous source under varying wind conditions. This capability allows assessing wind measurement uncertainties through a Monte Carlo analysis. To demonstrate the practical applicability, an interactive dashboard provides intuitive access to simulation results.

翻译：污染物扩散的数值模拟，例如化工厂气体泄漏事故后的模拟，能为应急响应和准备提供宝贵见解。模拟方法结合不可压缩Navier-Stokes (INS) 方程与平流-扩散 (AD) 过程来模拟风场和浓度场。然而，对于城市环境等复杂几何结构，此类高保真模拟的计算成本迅速增加，使其在时间敏感或多查询"假设"场景中不可行。因此，本研究聚焦于应用模型降阶 (MOR) 技术以实现快速而准确的预测。为此，针对计算要求更高、风速变化的参数化INS问题，对侵入式与非侵入式MOR方法进行了全面比较。基于这些见解，构建了一个同时考虑风速和风向的非侵入式降阶模型 (ROM)。研究在源自真实建筑足迹的二维域上进行，保留了分析（例如）较重污染物扩散的关键特征。所得ROM能够以快于实时的速度预测瞬时源在不同风条件下的时空污染物扩散。此能力允许通过蒙特卡洛分析评估风测量不确定性。为展示实际适用性，一个交互式仪表板提供了对模拟结果的直观访问。